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spice

The spice package can be used for calculating sequence-based protein features, visualizing the obtained features, and training and testing of protein classifiers using these features.

This featext.py module can be used for sequence-based protein feature extraction. it uses the featmat.py module to manage the labeled feature matrix, an m x n matrix for m proteins and n features, and the dataset.py module to manage the set of proteins and their corresponding labels.

The classification.py module is a layer on top of scikit-learn that can be used to construct protein classifiers and the classify.py module can be used to test new protein sequences on an allready trained classifier.

The project_management.py module is used by the SPiCE website to manage user projects.

Dependencies

The following software is required to run spice:

  • numpy >= 1.7.1
  • scipy >= 0.12.0
  • matplotlib >= 1.2.2
  • scikit-learn >= 0.14.1

The biopy package that can also be found on my github repository is also required:

  • biopy >= 0.1.0"

Install

On linux systems, the sofware can be installed using:

sudo python setup.py install

Usage

The software can be using the import statement, for example:

from spice import featext

Four command-line tools are also provided:

  • featext
  • classification
  • classify

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SPiCe - Sequence-based Protein Classification

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